A Spanish Financial Market Stress Index (FMSI)

Cambón, Ma Isabel; Estévez, Leticia Ameijide

doi:10.1016/j.srfe.2016.01.002

Cited by 20 publications

(4 citation statements)

References 20 publications

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“…for t = 1, 2, ... , n. The empirical CDF F n (x * ) measures the total number of observations x t not exceeding a particular value x * (which equals to the corresponding 11 See Cambón and Estévez (2016).…”

Section: Methodsmentioning

confidence: 99%

Measuring Liquidity of Spanish Debt

Cambón

Coello²,

Redondo

2017

SSRN Journal

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Assessing liquidity in fixed-income markets is becoming very important in the current context of extremely low interest rates which, in general terms, is encouraging the acquisition of riskier and (potentially) less liquid assets. Although there is the perception that bond market liquidity could have worsened over the last years in international markets, none of the current studies has reached a clear conclusion. In this paper, we propose a liquidity synthetic indicator (LSI) on Spanish debt, applying the methodology that Broto and Lamas (2016) used for US markets. We compute six individual liquidity indicators that represent the elements that characterise a liquid market (tightness, resilience, depth and breadth). We use price and transaction-based indicators for government and corporate debt when data is available for the period 2005-2016. Our LSI shows several episodes of significant worsening in liquidity conditions, related to the Lehman Brothers' collapse and the European sovereign debt crisis. After a sizeable improvement of liquidity in 2013-2014, the liquidity indicator has deteriorated over the past months as a consequence of lower trading volumes. The current ultralow interest rate environment and more capital demanding regulations could partially explain these results.

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Section: Methodsmentioning

confidence: 99%

Measuring Liquidity of Spanish Debt

Cambón

Coello²,

Redondo

2017

SSRN Journal

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“…In contrast to the market model strategy and the network model approach, the composite index model approach, which uses historical data to filter out key indicators affecting financial risk and to derive an index value reflecting the level of financial risk, has the advantage of not being dependent on the occurrence of financial crises in the past and can be applied to situations beyond a current financial crisis (Billio et al, 2012) to measure not only financial risk but also regional financial risk. To generate an index of financial risk, an index model is constructed by selecting risk indicators from the present condition of the financial markets in the United States, the European Union, and Spain, including the most representative micro indicators in the banking sector and the debt, stock, and foreign exchange markets (Camb on & Estévez, 2016). Based on this literature, this paper constructs an index system including the household sector, enterprise sector, financial sector, and government sector to measure financial risk.…”

Section: Financial Riskmentioning

confidence: 99%

Financial risk under the shock of global warming: Evidence from China

Gao,

Li,

Hao

2023

Bus Strat Env

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The economic and financial risks of global warming have become a hot issue of academic interest. This article analyzes global warming, financial risk, and the economic statistics of 30 provinces in China from 2010 to 2020 as a sample to assess the influence of the severity of global warming on financial risk. Global warming is found to affect financial risk and to have a substantial favorable influence on the amount of financial risk. Global warming also has significant effects on households, enterprises, financial institutions, and governments. There is heterogeneity in the effects of climate variation on financial risk. Global warming will cause a greater accumulation of financial risk in economically developed regions. Additionally, it will lead to financial risks by causing a decline in the incomes of residents, a decline in the profits of enterprises, growth in the number of loans that financial institutions consider to be nonperforming, and a widening of the gap between government revenue and expenditures. All of these effects will have an adverse domino effect on the economy. To reduce the financial risks caused by global warming, countermeasures are being offered to ensure social cohesion, conduct risk stress testing, create risk mitigation instruments, and encourage environmentally responsible development. This paper discusses policies and provides policymakers with recommendations on how to cope with the systematic financial risks induced by climate variation.

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“…The PCA which was developed by Pearson (1901) and Hotelling (1933) is a statistical technique which is widely used to generate a small number of artificial uncorrelated variables accounting for most of the variance of the initial multidimensional dataset, thereby arriving at condensed data representation with minimal loss of information (Sin , enko et al 2013). Each component is a linear combination of the original data and is ordered in such a way that the first component accounts for the largest share of the variance possible (see Cambón and Estévez 2016) for detailed mathematical notation). The PCA places more emphasis on variables with higher variances than on those with a low variance.…”

Section: Principal Component Analysis (Pca)mentioning

confidence: 99%

Financial Stress Index and Economic Activity in South Africa: New Evidence

Ilesanmi

Tewari

2020

Economies

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The importance of a sound and stable financial system and by extension economic stability was brought to the fore by the global financial crisis (GFC). The economic and social costs of the GFC have renewed the commitment of stakeholders in the financial sector including central banks to develop instruments and methodologies that will be useful in monitoring financial stress within the financial system and the real economy. This study contributes to the growing literature by developing a financial stress indicator for the South African financial market. The financial stress indicator (FSI) is a single aggregate indicator that is constructed to reflect the systemic nature of financial instability and also to measure the vulnerability of the financial system to both internal and external shocks. Using the principal component analysis (PCA), the results show that financial stress can be identified by the financial stress indicator. Furthermore, using a recursive Vector Autoregression (VAR) model to estimate the impact of financial stress on output and investment, the result shows that financial stress has a negative impact on economic growth and investment, though not immediately. FSI is very useful for gauging the effectiveness of government measures to mitigate the impact of financial stress. Concerted effort to stimulate investment and domestic production by relevant stakeholders is necessary to mitigate the impact of financial stress. This will go a long way to alleviating the impact of the financial stress on industrial production, employment and the economy at large.

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A Spanish Financial Market Stress Index (FMSI)

Cited by 20 publications

References 20 publications

Measuring Liquidity of Spanish Debt

Measuring Liquidity of Spanish Debt

Financial risk under the shock of global warming: Evidence from China

Financial Stress Index and Economic Activity in South Africa: New Evidence

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